Prior network science work on attacks against graphs was focused on attempts to disrupt infrastructure, e.g., disconnecting a power grid graph. In this area, it was shown that graphs with heterogeneous degree distributions (like BA and KR graphs) are much more robust to random node removals, but highly susceptible to targeted attacks against the nodes with the most connections [1]}.
